---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fine-tuned-arabert_mixdata_latest
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# fine-tuned-arabert_mixdata_latest

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1937
- Accuracy: 0.9572
- Precision: 0.9695
- Recall: 0.9612
- F1: 0.9653

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.159         | 1.0   | 64776  | 0.1417          | 0.9537   | 0.9620    | 0.9633 | 0.9627 |
| 0.1303        | 2.0   | 129552 | 0.1743          | 0.9551   | 0.9697    | 0.9575 | 0.9636 |
| 0.1135        | 3.0   | 194328 | 0.1615          | 0.9570   | 0.9652    | 0.9654 | 0.9653 |
| 0.0957        | 4.0   | 259104 | 0.1937          | 0.9572   | 0.9695    | 0.9612 | 0.9653 |


### Framework versions

- Transformers 4.19.3
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1